Search Results (354)

Japan’s 8.5 million vacant homes (Akiyas) represent a paradox of scarcity amid surplus: while rural depopulation leaves properties abandoned, housing shortages and bureaucratic inefficiencies hinder their reuse. This study proposes AKI2ALL, an AI-blockchain framework designed to automate the circular repurposing of Akiyas into ten high-value community assets—guesthouses, co-working spaces, pop-up retail and logistics hubs, urban farming hubs, disaster relief housing, parking lots, elderly daycare centers, exhibition spaces, places for food and beverages, and company offices—through smart contracts and data-driven workflows. By integrating circular economy principles with decentralized technology, AKI2ALL streamlines property transitions, tax validation, and administrative processes, reducing operational costs while preserving embodied carbon in existing structures. Municipalities list properties, owners select uses, and AI optimizes assignments based on real-time demand. This work bridges gaps in digital construction governance, proving that automating trust and accountability can transform systemic inefficiencies into opportunities for community-led, low-carbon regeneration, highlighting its potential as a scalable model for global vacant property reuse. Full article

Limited research has characterized the occurrence of organophosphate esters (OPEs) in indoor microenvironment air. To address this gap, ten OPE congeners were measured in air samples collected from 46 homes, 12 offices, 6 student dormitories, and 60 private cars in Guangzhou, China. Among the four microenvironments, private vehicles exhibited the highest total OPE concentrations (ΣOPEs), with an average of 264.89 ng/m³—statistically significantly higher than the other three environments (p < 0.05). This finding underscores the need for increased attention to OPE environmental fate in vehicles and associated human exposure risks. Distinct compositional profiles of OPEs were observed across microenvironments. In homes, offices, and student dormitories, tris(2-chloroethyl) phosphate (TCEP) and tris(2-chloropropyl) phosphate (TCPP) dominated the OPE mixture, accounting for 56% and 34% of ΣOPEs, respectively. By contrast, private cars were characterized by elevated levels of TCPP (68% of ΣOPEs) and tris(1,3-dichloro-2-propyl) phosphate (TDCP, 12%), reflecting source-specific emission patterns related to automotive materials. Significant correlations existed in most of the OPEs in the private cars, indicating that there are many potential sources of OPEs in private cars, and one source may release multiple OPEs. Human inhalation exposure to OPEs was estimated based on measured air concentrations. Daily respiratory exposure doses ranged from 9.1 to 30.85 ng/kg/d across different populations, with all values falling below established thresholds for non-carcinogenic and carcinogenic risks. These results indicate that current indoor air OPE levels in the studied microenvironments do not pose significant health hazards via inhalation pathways under typical exposure scenarios. Full article

The identification of vital signs is becoming increasingly important in various applications, including healthcare monitoring, security, smart homes, and locating entrapped persons after disastrous events, most of which are achieved using continuous-wave radars and ultra-wideband systems. Operating frequency and transmission power are important factors to consider when conducting earthquake search and rescue (SAR) operations in urban regions. Poor communication infrastructure can also impede SAR operations. This study proposes a method for vital sign detection using an integrated sensing and communication (ISAC) system where a unified orthogonal frequency division multiplexing (OFDM) signal was adopted, and it is capable of sensing life signs and carrying out communication simultaneously. An ISAC demonstration system based on software-defined radios (SDRs) was initiated to detect respiratory and heartbeat rates while maintaining communication capability in a typical office environment. The specially designed OFDM signals were transmitted, reflected from a human subject, received, and processed to estimate the micro-Doppler effect induced by the breathing and heartbeat of the human in the environment. According to the results, vital signs, including respiration and heartbeat rates, have been accurately detected by post-processing the reflected OFDM signals with a 1 MHz bandwidth, confirmed with conventional contact-based detection approaches. The potential of dual-function capability of OFDM signals for sensing purposes has been verified. The principle and method developed can be applied in wider ISAC systems for search and rescue purposes while maintaining communication links. Full article

Coaching is an important form of professional development for the early childhood education and care (ECEC) workforce. However, educators working in remote contexts do not always have access to this type of support. This paper explores the effectiveness of a virtual (online and telephone) coaching program focusing on the implementation of evidence-informed Conversational Reading strategies in supported playgroups for Aboriginal families in the Northern Territory of Australia. Fourteen Family Educators and Family Liaison Officers across ten Families as First Teachers playgroups in the Northern Territory participated in the coaching program over twelve months. Coaching records, planning documents, participant feedback, and video recordings of participants’ practice were analysed to explore the impact and acceptability of the coaching program. The findings indicate that participation in the cycle of virtual coaching, planning, and reflection supported participants in implementing evidence-informed teaching strategies, offering language-rich experiences to children frequently and with increased fidelity, and engaging with families about their use of these strategies in the home. The model of coaching developed shows promise for wider implementation in ECEC contexts, particularly in remote communities where access to high-quality professional learning and development can be limited. Full article

Background: We propose a framework for determining the stage of periodontitis in a personalized medicine context, building on our previously developed model for periodontitis detection. In this study, we improved the earlier model by incorporating additional components to form a comprehensive system for identifying both the presence and stage of periodontitis. Central to the home-use application is an active-matrix metalloproteinase-8 (aMMP-8) mouth rinse test (cut-off: 20 ng/mL), integrated with software delivered via a mobile application. Methods: First, using all the data, we modeled a single polynomial function to distinguish healthy and stage I periodontitis patients from stage II and III patients. Second, we used an already published periodontitis detection function to separate stage I patients from healthy patients. Third, one more function was created that divided stage II and III patients from each other. All functions were modeled by multiple logistic regression analysis from the patient data, which consisted of 149 adult patients visiting dental offices in Thessaloniki, Greece. Results: The complete model demonstrated a sensitivity of 95.8% (95% CI: 92.1–99.4%) and a specificity of 71.0% (95% CI: 55.0–86.9%) for detecting periodontitis. Among those identified with periodontitis, the correct stage was determined in 61.1% of cases, with stage-specific accuracies of 64.3% for stage I, 60.5% for stage II, and 60.9% for stage III. All testing was performed on patient data with which the complete model was formed. Conclusions: The results of this study showed that with sufficient data and using multiple logistic regression analysis, a model can be created to simultaneously identify the presence and stage of periodontitis. Overall, in the complete model generated, a mouth rinse aMMP-8 test result with a cut-off value of 20 ng/mL, Visible Plaque Index (VPI) and information of patient’s teeth number present were found to be important factors to determine the stage of periodontitis in a personalized medicine manner for everyone to use. Full article

Background: The United States has the highest number of immigrants in the world, with over 46 million foreign-born residents as of 2022. A growing number of migrants originate from Latin America, driven by factors such as economic instability, food insecurity, and crime. This study explores their experiences and perceptions regarding trust in the criminal justice system (CJS) in both their home countries and the United States. Methods: This study surveyed 500 migrants at a transitional institution in a U.S.–Mexico border city in the summer of 2023. The survey assessed confidence in law enforcement, immigration officers, courts, and government institutions using a 5-point Likert scale. Results: Migrants reported significantly higher confidence in the U.S. CJS compared to that of their home countries. Multivariate analysis revealed that satisfaction with border officials, documentation status, English proficiency, and health were positively associated with confidence in the U.S. CJS, while employment status, traveling with family, and fear of crime correlated with lower confidence. Conclusions: This study highlights the stark contrast in migrants’ confidence levels between their home countries and the U.S. criminal justice system. While migrants view the U.S. system as more legitimate, challenges such as fear of crime and legal uncertainties persist. Full article

The most common anorectal disorders are fecal incontinence, functional anorectal pain, and functional defecation disorders. They are often presented by overlapping symptoms with various degrees of severity. Therefore, a personalized approach to the patient is crucial for diagnosing and determining the prognosis of the disease. Biofeedback training is appropriate to consider when the motoric function disorder is known, the patient could learn voluntary control of response, and this could further lead to an improvement in the condition. Biofeedback is recommended for short-term and long-term treatment of constipation in adults and fecal incontinence in adults. It could also be considered for treatment of specific cases of anorectal pain. As office biofeedback is often time-consuming and comes with a substantially high cost, there is an emerging trend of home biofeedback administration. However, only a few significant studies have been published on this new approach. Although comprehensive data are needed to evaluate the proper strategy and development of various treatment protocols for different types of defecation disorders, home biofeedback therapy offers a potentially effective tool in the personalized treatment of defecation disorders. Full article

Since its introduction, optical coherence tomography (OCT) has significantly progressed in addressing its limitations. By integrating artificial intelligence and multimodal imaging, OCT enhances both speed and image quality while reducing its size. OCT continues to advance, offering new possibilities beyond the in-office setting, including intraoperative applications. This review will explore the different types of home OCT and intraoperative OCT, as well as the uses of each device and their future potential in ophthalmology. Full article

The COVID-19 pandemic increased the number of video conferences, for example, through online teaching and home office meetings. Even in the medical environment, consultation sessions are now increasingly conducted in the form of video conferencing. This includes sessions between psychotherapists and one or more call participants (individual/group calls). To subsequently document and analyze patient conversations, as well as any other human–human dialog, it is possible to record these video conferences. This allows experts to concentrate better on the conversation during the dialog and to perform analysis afterward. Artificial intelligence (AI) and its machine learning approach, which has already been used extensively for innovations, can provide support for subsequent analyses. Among other things, emotion recognition algorithms can be used to determine dialog participants’ emotions and record them automatically. This can alert experts to any noticeable sections of the conversation during subsequent analysis, thus simplifying the analysis process. As a result, experts can identify the cause of such sections based on emotion sequence data and exchange ideas with other experts within the context of an analysis tool. Full article

Occupancy monitoring (OM) and the localization of individuals within indoor environments using wearable devices offer a very promising data communication solution in applications such as home automation, smart office management, outbreak monitoring, and emergency operating plans. OM is challenging when developing solutions that focus on reduced power consumption and cost. Bluetooth low energy (BLE) technology is energy- and cost-efficient compared to other technologies. Integrating BLE Received Signal Strength Indicator (RSSI) signals with machine learning (ML) introduces a new Artificial Intelligence- (AI-) enhanced OM approach. In this paper, we propose an Intelligent Bluetooth Virtual Door (IBVD) OM system for the indoor/outdoor tracking of individuals using the interaction between a BLE device worn by the occupant and two BLE beacons located at the entrance/exit points of a doorway. ML algorithms are used to perform intelligent OM through pattern detection from the BLE RSSI signal(s). This approach differs from other technologies in that it does not require any floorplan information. The developed OM system achieves a range between 96.6% and 97.3% classification accuracy for all tested ML models, where the error translates to a minor delay in the time in which an individual’s location is classified, introducing a highly reliable indoor/outdoor tracking system. Full article

This paper presents a novel unsupervised domain adaptation (UDA) framework that integrates information-theoretic principles to mitigate distributional discrepancies between source and target domains. The proposed method incorporates two key components: (1) relative entropy regularization, which leverages Kullback–Leibler (KL) divergence to align the predicted label distribution of the target domain with a reference distribution derived from the source domain, thereby reducing prediction uncertainty; and (2) measure propagation, a technique that transfers probability mass from the source domain to generate pseudo-measures—estimated probabilistic representations—for the unlabeled target domain. This dual mechanism enhances both global feature alignment and semantic consistency across domains. Extensive experiments on benchmark datasets (OfficeHome and DomainNet) demonstrate that the proposed approach consistently outperforms State-of-the-Art methods, particularly in scenarios with significant domain shifts. These results confirm the robustness, scalability, and theoretical grounding of our framework, offering a new perspective on the fusion of information theory and domain adaptation. Full article

This study examines the factors influencing home elevation decisions among participants in Houston’s Homeowner Assistance Program (HoAP) and the Texas General Land Office’s Homeowner Assistance Program (HAP) in the aftermath of Hurricane Harvey and other flood events. Using a mixed-methods approach, we conducted surveys and semi-structured interviews with 50 homeowners, supplemented by secondary data analyses of program records and GIS-based flood risk assessments. Additionally, 25 undergraduate students engaged in a structured field trip, conducting site observations, interacting with residents, and discussing home elevation with experts. The findings reveal disparities in home elevation outcomes, with lower completion rates in socially vulnerable neighborhoods despite program eligibility. The study also identifies key factors influencing elevation decisions, including mobility concerns, financial constraints, neighborhood esthetics, and perceptions of long-term flood risk. Homeowners aged 60–79 were more likely to elevate their homes, while individuals with disabilities faced additional barriers. This research highlights the need for targeted policy interventions to improve program equity and ensure that vulnerable populations receive adequate support. Beyond its case study implications, this research contributes to broader discussions on disaster recovery, climate adaptation, and urban resilience. It also serves as a model for integrating student learning into community-based participatory research. While this study is limited in scope, it offers insights into the intersection of social vulnerability and housing adaptation, informing future policy efforts to enhance flood resilience in historically marginalized communities. Full article

Health professionals are trusted information sources and could be valuable for improving climate change health literacy. Few studies address teaching patients about health risks associated with climate change, and no studies have focused on the medical office waiting room as a teaching site for populations from heat-vulnerable neighborhoods. We gave adult patients in primary care office waiting rooms printed teaching materials about heat-related illnesses. We asked them to read these at home and then complete an online confidential survey concerning their preferences among teaching methods and their preferences for communication during health emergencies. Ninety-one surveys were received from patients residing in heat-vulnerable neighborhoods. Patients liked receiving information in waiting rooms. Printed brochures were favored statistically by patients, but other teaching methods that are feasible for waiting rooms also rated well, including single-page printed fliers, posters, and video screens. Digital options were far less favored. We conclude that printed teaching materials may improve decisions that impact human health. The medical office waiting room appears to be an accepted, time-efficient, and effective site to communicate knowledge on climate change and health. Additionally, medical offices could play a role supporting government agencies to communicate with patients during weather-related health emergencies. Full article

There are over 300 million smart homes worldwide and 60.4 million smart homes in the US, using devices like smart thermostats, smart plugs, smart door locks, etc. Yet in this age of smart and connected devices, we still use paper-based sticky notes on doors to display messages such as “Busy, do not disturb”, “In a Zoom meeting”, etc. In this project, a novel IoT-connected digital sticky note system was developed where the user can wirelessly send messages from a smartphone to a sticky note display. The sticky note displays can be hung on the doors of offices, hotels, homes, etc. The display could be updated with the user’s message sent from anywhere in the world. The key design challenge was to develop the display unit to consume as little power as possible to increase battery life. A prototype of the proposed system was developed comprising ultra-low-power sticky note display units consuming only 404 µA average current and having a battery life of more than six months, with a Wi-Fi-connected hub unit, an MQTT server, and a smartphone app for composing the message. Full article

It is a serious challenge for humanity to find an appropriate response to stop the accelerating rise in global temperature caused by atmospheric carbon dioxide emissions. After a methodological review of the literature, online and in-person modelling of education, work, and conferences, and relying on the results of life-cycle studies, we sought the answer to what reasonable solutions are available for decarbonization and energy reduction. During the research, the organizational carbon footprint of a selected office, educational institution and conference, and then the carbon footprint created by a person in 1 h, were examined. The two-day online education significantly reduced the daily commute load in transport by 402 tons of CO₂ equivalent per year. Still, the energy demand of home learning subtracts 136 tons from this, so the real benefit was 266 tons above in an institution educating nearly 3500 students. In a workplace of 180 people, where 52% of employees commute, 90% teleworking saved 222 tons of carbon dioxide emissions in one month, taking into account the carbon footprint of working from home. In the case of conferences, the online solution reduces the carbon footprint due to the absence of travel and catering. Comparing the three areas, for the in-person case, the conference’s carbon footprint per person per hour was the highest (11.91 kg CO₂ eq.). This value for education was 1.15 kg CO₂ eq.; for work, it was the lowest with a value of 0.90 kg CO₂ eq. Moving to an online space resulted in the most significant savings for the conference (11.55 kg CO₂ eq.), followed by working (0.54 kg CO₂ eq.), and minor savings were achieved in hybrid education (0.13 kg CO₂ eq.). The sensitivity analysis highlighted the impact of transport on carbon footprint in all three cases. However, the life cycle cost analysis showed that moving to a virtual space reduces the life cycle cost of de-carbonization by 42%. Full article